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Industrial and Systems Engineering

Professors. Keith M. Gardiner, Ph.D. (Manchester); Nicholas G. Odrey, Ph.D. (Penn State); Robert H. Storer, Ph.D. (Georgia Tech); Tamás Terlaky, Ph.D. (Loránd Eötvös Univ.) chair; S. David Wu, Ph.D. (Penn State); Emory W. Zimmers, Jr., Ph.D. (Lehigh).

Associate Professors. Eugene Perevalov, Ph.D. (TexasAustin); Louis J. Plebani, Ph.D. (Lehigh); Theodore K. Ralphs, Ph.D. (Cornell); Katya A. Scheinberg, Ph.D. (Columbia); Lawrence V. Snyder (Northwestern); Aurélie Thiele, Ph.D. (MIT); Gregory L. Tonkay, Ph.D. (Penn State); George R. Wilson, Ph.D. (Penn State) associate chair.

Assistant Professors. Frank E. Curtis (Northwestern); Luis F. Zuluaga, Ph.D. (Carnegie Mellon).

Professors of Practice. Hisham Abu-Nabaa, M.S. (Wilkes); Pasquale Costa, B.S. (Penn State).

Professors Emeritus. Mikell P. Groover, Ph.D. (Lehigh); John W. Adams, Ph.D. (North Carolina).

Mission Statement

To pursue excellence and national prominence in the areas of manufacturing, operations research, information technology and related fields of industrial engineering through innovative teaching, distinguished research and scholarship, and active professional leadership. Building on its unique strength and national reputation in undergraduate education and industrial research, the department strives for leadership in educational innovation, multidisciplinary research, and industrial partnership. Our ultimate mission is to produce leaders who have learned to think critically and analytically, have the skills and techniques to comprehend and create new knowledge, and are willing to serve and inspire others.

Physical Facilities

The industrial and systems engineering department is located in the Harold S. Mohler Laboratory at 200 West Packer Avenue at the northwest corner of the Lehigh University Asa Packer campus. The Mohler Lab building contains the classrooms, laboratories, and faculty offices of the department. Labs in the Mohler Laboratory building include:

Computational Optimization Research @ Lehigh (COR@L) Lab. The COR@L lab consists of high performance computer workstations, each equipped with state-of-the-art commercial and noncommercial software for large-scale numerical optimization. COR@L is used for both research and instruction.

Enterprise Systems Center Laboratories. The ESC Laboratories contain a variety of computer systems and software in support of agility in Computer Integrated Manufacturing (CIM) and in engineering logistics and distribution problem solving, including: Computer Aided Design (CAD) and Engineering (CAE), discrete event simulation, linear and nonlinear optimization, Finite Element Analysis (FEA), facilities design, process design, and process control.

Manufacturing Technology Laboratory (MTL). The MTL contains equipment for instruction and research in manufacturing processes, numerical control (NC), NC part programming, material handling and storage, industrial control systems, and metrology.

Automation and Robotics Laboratory. This lab contains a variety of industrial robots and other automated systems to provide students with -hands-on experience in the planning and use of this kind of equipment.

Work Systems Laboratory. This classroom/laboratory affords the opportunity for undergraduate students to analyze and plan human work activities for individual workstations and worker team situations. A full scale manual assembly line is available for study.

Considerable use is made of university computer facilities in IE coursework. IE/computing center PC laboratories containing 54 PCs are located in the Mohler Laboratory building.

B.S. in Industrial Engineering

Industrial Engineering (IE) is concerned with the analysis, design, and implementation of integrated systems of people, materials, information, and equipment to accomplish useful work. The discipline of industrial engineering is applicable in nearly all industries, whether the industry involves manufacturing of a product or delivery of a service. Job functions performed by IEs include: systems analysis, cost estimation, capital equipment selection, engineering economy, facilities planning, production planning and scheduling, inventory control, quality control, information systems, project management, operations management, engineering management, as well as methods analysis and work measurement. Manufacturing systems engineering (MSE) is a specialty field associated with industrial engineering that emphasizes functions and technologies such as process planning, plant layout design, manufacturing resource planning, production management, production line design, automation, robotics, flexible manufacturing systems, and computer integrated manufacturing.

Career Opportunities

IE graduates are sought by nearly all industrial corporations as well as government agencies and other service institutions. Major employers of our graduates include management consulting firms, manufacturing companies, banks, hospitals, railroads, the postal service, and transportation/logistics services. A typical career path of an industrial engineer is to start in an entrylevel engineering position or as a technical analyst and to progress through various management positions in the firm or institution. Significant numbers of industrial engineers ultimately become chief executive officers, chief operating officers, and chief technology officers in their respective organizations.

Program Educational Objectives

Industrial Engineering graduates will:

1. recognize and analyze problems, design innovative solutions, and lead their implementation

2. excel as industrial and systems engineering professionals who are able to operate effectively in a global, culturally diverse society

3. communicate effectively using written, oral, and electronic media

4. pursue lifelong learning and professional growth as ethical and responsible members of society

5. form, lead, and participate on multidisciplinary teams that solve problems in engineering and business

IE Curriculum

The IE curriculum is designed to provide graduates with the skills and knowledge that employers expect of young industrial engineers beginning their professional careers, and to instill the ability for lifetime learning. It includes the basic mathematical, physical, and social sciences, together with the principles and methods of engineering analysis and design that are specific to industrial engineering. These principles and methods include probability and statistics, engineering economy, cost accounting, operations research, computer simulation, work methods and measurement, manufacturing processes, production and inventory control, and information technology.

Specialized industrial engineering electives in the senior year include: advanced optimization models, stochastic models, operations research, operations management, organization planning and control, statistical quality control, database design, web technologies, and data communications technologies. Electives related to manufacturing systems engineering include: industrial robotics, facilities planning and material handling, logistics and supply chain, production engineering, and metal machining analysis. The ISE department website contains a list of optional tracks and course suggestions for IE majors interested in specific fields ( http://www.lehigh.edu/ise ). The IE degree requires a minimum of 130 credit hours.

IE Major Requirements

See freshman year requirements, section III. An HSS course is assumed to be taken in the freshman year in the following semester course plans.

sophomore year, first semester (16 credit hours)

IE 111 Engineering Probability (3)

IE 112 Computer Graphics (1)

MATH 23 Calculus III (4)

PHY 21, 22 Introductory Physics II and Laboratory (5)

MAT 33 Engineering Materials and Processes (3)

sophomore year, second semester (17 credit hours)

junior year, first semester (16-18 credit hours)

junior year, second semester (17-18 credit hours)

summer

senior year, first semester (18 credit hours)

senior year, second semester (15 credit hours)

Notes:

*HSS elective credit totals must satisfy the college HSS program

**IE elective courses are chosen from the current offering of 300-level IE courses

***The Engineering Requirement may be satisfied by choosing from the following list: MECH 2 (or 3, but not both), ME 104, ECE 83 (or 81, but not both), CSE 17, CEE 170, or CHE 44

Special Opportunities for IE students

The following special opportunities are available to majors in industrial engineering and information & systems engineering:

Nontechnical Minor. Students may choose to pursue a nontechnical minor in an area of the humanities, social sciences, business, or entrepreneurship. Students in the business minor can satisfy the ACCT 108 requirement by completing BUS 127.

Technical Minor. Technical minors such as engineering leadership, materials science, environmental engineering, and computer science are available through departments in the P. C. Rossin College of Engineering and Applied Science. Consult the specific department for more details.

Graduate Courses. Seniors in industrial and systems engineering can petition to take up to two graduate IE courses (400level) to satisfy two of their four 300level elective IE course requirements. The petitioning senior must have a good scholastic record (generally above a 3.0 GPA).

Senior Thesis Option. Students interested in continuing on to graduate school or performing research are encouraged to take the senior thesis option. In this option a student takes IE 155 as an engineering or free elective. After IE 155, IE 156 is taken as the thesis is written. The sequence of these 2 courses can replace IE 154.

Technical Minor in Engineering Leadership

The minor in engineering leadership provides students with the background and practice to become more effective leaders. The minor consists of 5 courses that explore different aspects of leadership. Additional details can be found on the Engineering Leadership Minor website (http://www.lehigh.edu/~inleader/).

Technical Minor in Manufacturing Systems Engineering

The minor in manufacturing systems engineering provides a concentration of courses in the manufacturing and production areas. This minor is not available to students majoring in industrial engineering. It requires 16 credits.

5th Year Master of Management Science and Engineering Option

Students enrolled in the IE or ISE curricula can pursue a fifthyear Master of Management Science and Engineering program. Students in the management science program take a mixture of engineering and business courses. Admission is not guaranteed. For details see the management science and engineering section of the catalog or contact the ISE department.

Graduate Programs

Several programs leading to master's and doctoral degrees are offered by the Department of Industrial and Systems Engineering. Each program has core requirements. Core requirements can be satisfied by previous coursework upon petition of the ISE graduate committee. All core course prerequisites must also be satisfied. Prerequisites may be satisfied by (1) previous course work, (2) completing the prerequisite course without graduate credit, or (3) passing the final examination of the prerequisite course with a grade of B or better.

A Ph.D. student is required to complete core requirements with grades of B or better before being formally admitted to Ph.D. candidacy.

Further information about graduate programs is contained in an ISE graduate brochure available from the department. In addition, documents are available from the department that describe the requirements of each graduate program.

Certificate in Quality Engineering

The quality engineering certificate program provides students with the background necessary to analyze, propose and implement changes to improve the quality of products or the efficiency of service systems. The certificate requires four specified courses. Details can be found on the ISE Department website and in the ISE office.

M.S. in Industrial and Systems Engineering

The minimum program for the master of science degree in Industrial and Systems Engineering consists of 24 credit hours of approved coursework and completion of a satisfactory thesis. Courses in other departments for which the student has the prerequisites may be integrated into this program. Subject to advisor approval, up to nine credit hours of 300 and 400-level courses from other departments may be included in the Industrial and Systems Engineering masters program. The other department courses usually include other engineering disciplines, mathematics, computer science, and business and economics.

M.Eng. in Industrial and Systems Engineering

This program of study is for those students whose interests are toward engineering design rather than research. The program provides opportunity to gain greater breadth of field through 30 credit hours of coursework (which can include a 3-credit-hour project).

M.S. in Management Science and Engineering

See separate catalog listing under Management Science and Engineering.

M.Eng. in Management Science and Engineering

See separate catalog listing under Management Science and Engineering.

M.S. in Manufacturing Systems Engineering

This is an interdisciplinary graduate program leading to the master of science degree in manufacturing systems engineering. See separate catalog listing under Manufacturing Systems Engineering.

M.Eng. in Healthcare Systems Engineering

This concentrated degree program is designed to prepare graduate students for engineering and management careers in firms engaged in delivering healthcare and health related products and services. See separate catalog listing under Healthcare Systems Engineering.

Ph.D. in Industrial Engineering

The graduate program leading to the doctor of philosophy (Ph.D.) degree is organized to meet the individual goals and interests of graduate students whose professional plans include teaching, consulting, or research in an educational, governmental, or industrial environment. Each doctoral candidate is required to demonstrate: (1) a high level of proficiency in one or more fields of industrial and systems engineering, and (2) a capacity for independent research through the preparation of a dissertation related to his/her field of specialization.

This is to be facilitated as follows. During the first year of study, all Ph.D. students must complete the following core courses (or a substitute approved by the Ph.D. program coordinator): IE 406, IE 429, Math 301, and Math 338 or ECO 416. At the end of the first year, each student must declare one of the following two methodological fields of study:

• Optimization, or

• Applied Probability and Statistics

and an applied field, such as

• Financial Engineering,

• Computational Engineering,

• Manufacturing, Production and Logistics,

• A custom-designed program in another applied field (with approval of the Ph.D. program coordinator).

In addition to the core courses, three courses in each of the two declared fields of study are required. Following the first year, an initial review, consisting of faculty evaluation, classroom performance, and a qualifier exam, must be passed. A review by the student’s dissertation committee must be passed in each subsequent year, along with the required dissertation proposal and general exam.

Undergraduate Courses

IE 100. Industrial Employment (0)

Usually following the junior year, students in the industrial engineering curriculum are required to do a minimum of eight weeks of practical work, preferably in the field they plan to follow after graduation. A report is required. Prerequisite: Sophomore standing.

IE 111. Engineering Probability (3) fall and spring

Random variables, probability models and distributions. Poisson processes. Expected values and variance. Joint distributions, covariance and correlation. Prerequisite: MATH 22.

IE 112. Computer Graphics (1) fall

Introduction to interactive graphics and construction of multiview representations in twoand threedimensional space. Applications in industrial engineering. Prerequisites: Sophomore standing in industrial engineering.

IE 121. Applied Engineering Statistics (3) spring

The application of statistical techniques to solve industrial problems. Regression and correlation, analysis of variance, quality control, and reliability. Prerequisite: IE 111 or MATH 231.

IE 131 Work Systems and Operations Management (3) spring

Workermachine systems, work flow, assembly lines, logistics and service operations, and project management. Operations analysis, methods engineering, work measurement, lean production, and six sigma. Workplace ergonomics, plant layout design, and work management. Prerequisite: IE 111 or equivalent, either previously or concurrently.

IE 132. Work Systems Laboratory (1) spring

Laboratory exercises, case studies, and projects in operations analysis, methods engineering, work measurement, and plant layout design. Corequisite: IE 131.

IE 154. Senior Project (3) fall and spring

The use of industrial engineering techniques to solve a major problem in either a manufacturing or service environment. Problems are sufficiently broad to require the design of a system. Human factors in system design. Laboratory. Prerequisite: Senior standing in industrial engineering.

IE 155. Senior Thesis I (3)

In depth study of a research topic in industrial engineering supervised by an ISE department faculty member. Requires completion of a formal research proposal and a public presentation of the proposal at the end of the semester. Prerequisite: Senior standing.

IE 156. Senior Thesis II (3)

Continued in depth study of a research topic in industrial engineering supervised by an ISE department faculty member. Requires a formal thesis and public presentation of the results. IE 156 can be substituted for IE 154 in the IE curriculum when taken in sequence after IE155. Prerequisite: IE 155.

IE 168. Production Analysis (3) spring

A course for students not majoring in industrial engineering. Engineering economy; application of quantitative methods to facilities analysis and planning, operations planning and control, work measurement, and scheduling. Prerequisites: MATH 21 or 51.

IE 172. Algorithms in Systems Engineering (4) spring

Use of computers to solve problems arising in systems engineering. Design and implementation of algorithms for systems modeling, systems design, systems analysis, and systems optimization. Computer systems, basic data structures, the design and implementation of efficient algorithms, and application of algorithms to the design and optimization of complex systems such as those arising in transportation, telecommunications, and manufacturing. Weekly laboratory with exercises and projects. Prerequisite: CSE 17 or CSE 18.

IE 185. ISELP Honors Seminar (1)

Study of problem solving, principles of enterprise systems, and creative use of information technology in controlled environments. Emphasis on teamwork, self knowledge, and communication skills. Department permission required. May be repeated for credit.

For Advanced Undergraduates and Graduate Students

IE 215. Fundamentals of Modern Manufacturing (3) fall

Manufacturing processes and systems. Metal machining and forming, polymer shape processes, powder metallurgy, assembly and electronics manufacturing. Introduction to automation, numerical control, and industrial robots. Prerequisite: MAT 33.

IE 216. Manufacturing Laboratory (1) fall

Laboratory exercises and experiments in manufacturing processes and systems. Prerequisite or concurrent: IE215.

IE 224. Information Systems Analysis and Design (3) spring

An introduction to the technological as well as methodological aspects of computer information systems. Content of the course stresses basic knowledge in database systems. Database design and evaluation, query languages and software implementation. Students that take CSE 241 cannot receive credit for this course.

IE 226. Engineering Economy and Decision Analysis (3) spring

Economic analysis of engineering projects; interest rate factors, methods of evaluation, depreciation, replacement, breakeven analysis, aftertax analysis. decision-making under certainty and risk. Prerequisite: IE 111 or MATH 231, either previously or concurrently.

IE 230 Introduction to Stochastic Models in Operations Research (3)

Formulating, analyzing, and solving mathematical models of real-world problems in systems exhibiting stochastic (random) behavior. Discrete and continuous Markov chains, queueing theory, inventory control, Markov decision process. Applications typically include traffic flow, call centers, communication networks, service systems, and supply chains. Prerequisites: IE 111 or Math 231.

IE 240 Introduction to Deterministic Optimization Models in Operations Research (3)

Formulating, analyzing, and solving mathematical models of real-world problems in systems design and operations. A focus on deterministic optimization models having parameters that are known and fixed. Algorithmic approaches for linear, integer, and nonlinear problems. Solving optimization problems utilizing specialized software. Prerequisite: Math 205 or consent of instructor

IE 251. Production and Inventory Control (3) fall

Techniques used in the planning and control of production and inventory systems. Forecasting, inventory models, operations planning, and scheduling. Prerequisites: IE 121, IE 230, and IE 240.

IE 275. Fundamentals of Web Applications (3)

Introduction to web technologies required to support the development of client side and server side components of Internet based applications. Students will be exposed to the problems of design, implementation, and management by way of assigned readings, class discussion, and project implementation. Term project. Prerequisites: either IE 224 or CSE 241 previously or concurrently.

IE 281. Leadership Project (1-3)

Application of leadership principles through team projects with industry. Written report required. (Prerequisite: IE 382 or permission of instructor).

IE 305. Simulation (3)

Applications of discrete and continuous simulation techniques in modeling industrial systems. Simulation using a highlevel simulation language. Design of simulation experiments. Prerequisite: IE 121.

IE 316. Optimization Models and Applications (3)

Modeling and analysis of operations research problems using techniques from mathematical programming. Linear programming, integer programming, multicriteria optimization, stochastic programming, and nonlinear programming using an algebraic modeling language. Prerequisite: IE 240 or equivalent.

IE 319. Facilities Planning and Material Handling (3)

Facilities planning including plant layout design and facility location. Material handling analysis including transport systems, storage systems, and automatic identification and data capture. Prerequisite: IE 131 or consent of department chair.

IE 321. Independent Study in Industrial & Systems Engineering (1-3)

Experimental projects in selected fields of industrial engineering, approved by the instructor. A written report is required. May be repeated for academic credit. Department permission required.

IE 324. Industrial Automation and Robotics (3)

Introduction to robotics technology and applications. Robot anatomy, controls, sensors, programming, work cell design, part handling, welding, and assembly. Laboratory exercises. Prerequisites: MATH 205 and Senior Standing.

IE 328. Engineering Statistics (3)

Random variables, probability functions, expected values, statistical inference, hypothesis testing, regression and correlation, analysis of variance, introduction to design of experiments, and fundamentals of quality control. Prerequisite: MATH 23 or equivalent. This course cannot be taken by IE undergraduates.

IE 332. Product Quality (3)

Introduction to engineering methods for monitoring, control, and improvement of quality. Statistical models of quality measurements, statistical process control, acceptance sampling, and quality management principles. Some laboratory exercises. Prerequisite: IE 121.

IE 334. Organizational Planning and Control (3) fall

Design of organization and procedures for managing functions of industrial engineering. Analysis and design of resources planning and control, including introduction of change in manmachine systems; manpower management and wage administration. Prerequisite: Junior Standing.

IE 339. Stochastic Models and Applications (3)

Introduction to stochastic process modeling and analysis techniques and applications. Generalizations of the Poisson process; renewal theory and applications to inventory theory, queuing, and reliability; Brownian motion and stationary processes. Prerequisite: IE 230 or equivalent.

IE 340. Production Engineering (3) fall

Development of process plans for manufacturing of discrete parts. Emphasis on machining processes planning and design manufacturing interface. Economic analysis of process design alternatives. Concurrent engineering topics. Introduction to mechanization, automation, and flexible manufacturing systems. Fundamentals of group technology and cellular manufacturing Term project. Laboratory. Prerequisite: IE 215.

IE 341. Data Communication Systems Analysis and Design (3)

An introduction to the hardware as well as performance evaluation of data communication networks. Emphasis on data transmission, encoding, data link control, communication networking techniques, and queuing/simulation analysis of network performance. Prerequisite: IE 224, IE 230, and IE 240 or equivalent.

IE 344. (MAT 344/ME 344) Metal Machining Analysis (3) spring

Intensive study of metal cutting emphasizing forces, energy, temperature, tool materials, tool life, and surface integrity. Abrasive processes. Laboratory and project work. Prerequisite: IE 215 or ME 240 or Mat 206.

IE 345. Manufacturing Information Systems (3)

A study of contemporary Information Technology solutions used to support the manufacturing function from product concept and design through production planning, manufacture, and delivery. Emphasis will be placed on information exchange protocol standards used to improve the overall integration of manufacturing systems. Prerequisites: IE275.

IE 347 Financial Optimization (3)

Making optimal financial decisions under uncertainty. Financial topics include asset/liability management, option pricing and hedging, risk management and portfolio optimization. Optimization techniques covered include linear and nonlinear optimization, discrete optimization, dynamic programming and stochastic optimization. Emphasis on use of modeling languages and solvers in financial applications. Requires basic knowledge of linear optimization and probability. Credit will not be given for both IE 347 and IE 447. Prerequisite: IE 316 or equivalent

IE 355. Optimization Algorithms and Software (3)

Basic concepts of large families of optimization algorithms for both continuous and discrete optimization problems. Pros and cons of the various algorithms when applied to specific types of problems; information needed; whether local or global optimality can be expected. Participants practice with corresponding software tools to gain hands-on experience. Credit will not be given for both IE 355 and IE 455. Prerequisite: IE 240 or consent of instructor

IE 356 Introduction to Systems Engineering and Decision Analysis (3)

Systems Engineering modeling techniques. Architectures for large scale systems design. Includes physical, functional, and operational architectures. Requirements engineering, interface and integration issues, graphical modeling techniques. Additional topics may include: decision analysis techniques for systems, uncertainty analysis, utility functions, multiattribute utility functions and analysis, influence diagrams, risk preference, Analytical Hierarchy and Node Processes in decision making. Prerequisites: IE 230 and IE 240 or consent of instructor

IE 358. (ECO 358). Game Theory (3)

A mathematical analysis of how people interact in strategic situations. Applications include strategic pricing, negotiations, voting, contracts and economic incentives, and environmental issues. Prerequisites: ECO 105 or 115 and MATH 21, 31 or 51.

IE 362. (MSE 362). Logistics and Supply Chain Management (3)

Modeling and analysis of supply chain design, operations, and management. Analytical framework for logistics and supply chains, demand and supply planning, inventory control and warehouse management, transportation, logistics network design, supply chain coordination, and financial factors. Students complete case studies and a comprehensive final project. Prerequisite: IE 230 and IE 240 or equivalents, or instructor approval.

IE 372. Systems Engineering Design (3)

Analysis, design, and implementation of solutions to problems in manufacturing and service sectors using information technology. Emphasis on problem identification and the evaluation of proposed solutions and implementations. Term Project. Prerequisites: IE 230, IE 240, and IE 275.

IE 382. Leadership Development (3) spring

Exploration and critical analysis of theories, principles, and processes of effective leadership. Managing diverse teams, communication, and ethics associated with leadership. Application of knowledge to personal and professional life through projects and team assignments. (Junior or Senior)

IE 385. ISELP Honors Project Seminar (1)

Application of problem solving to real enterprise systems projects. Emphasis on leadership, teamwork, design, and communication skills. Requires a written honors project report. Department permission required. Senior standing. May be repeated for credit.

Graduate Courses

IE 404. Simulation (3)

Applications of discrete and continuous simulation techniques in modeling industrial systems. Simulation using a highlevel simulation language. Design of simulation experiments. This course is a version of IE 305 for graduate students, with research projects and advanced assignments. Prerequisites: IE 121 or IE 328 or equivalent.

IE 405. Special Topics in Industrial & Systems Engineering (3)

An intensive study of some field of industrial & systems engineering.

IE 406. Introduction to Mathematical Optimization (3)

Algorithms and techniques for the solution and analysis of deterministic linear optimization models used in operations research. Linear and integer linear optimization problems. Modeling techniques and fundamental algorithms and their complexity properties. Available open source and commercial solvers discussed.

IE 408. Management of Information Systems (3)

Philosophies and methods for systematic planning, development, and implementation of management information systems. Concepts of information resource management, and strategic and longrange planning of information systems and services. Prerequisite: IE 224 or ACCT 311 or equivalent.

IE 409. Time Series Analysis (3)

Theory and applications of an approach to process modeling, analysis, prediction, and control based on an ordered sequence of observed data. Single or multiple time series are used to obtain scalar or vector difference/ differential equations describing a variety of physical and economic systems. Prerequisite: IE 121 or equivalent.

IE 410. Design of Experiments (3)

Experimental procedures for sorting out important causal variables, finding optimum conditions, continuously improving processes, and trouble shooting. Applications to laboratory, pilot plant and factory. Prerequisite: Some statistical background and experimentation in prospect, IE 121 or equivalent.

IE 411. Networks and Graphs (3)

This course examines the theory and applications of networks and graphs. Content of the course stresses on the modeling, analysis and computational issues of network and graph algorithms. Complexity theory, trees and arborescences, path algorithms, network flows, matching and assignment, primaldual algorithms, Eulerian and Hamiltonian walks and various applications of network models. Prerequisite: IE 406 or equivalent.

IE 412. Quantitative Models of Supply Chain Management (3)

Analytical models for logistics and supply chain coordination. Modeling, analysis, and computational issues of production, transportation, and other planning and decision models. Logistics network configuration, risk pooling, stochastic decision-making, information propagation, supply chain contracting, and electronic commerce implication. Prerequisite: IE 316 and IE 339, or equivalent.

IE 413. Advanced Engineering Economy and Replacement Analysis (3)

Measuring economic worth, economic optimization under constraints, analysis of economic risk and uncertainty. Emphasis on analytical methods to evaluate the economic desirability of replacement and retirement options in capital investment. Prerequisites: IE 230, IE 240, and IE 226, or equivalents.

IE 414. Heuristic Methods in Combinatorial Optimization (3)

Heuristic methods for solving combinatorial and discrete optimization problems such as routing, scheduling, partitioning and layout. Introduction to NPcompleteness theory, exact and inexact methods, performance analysis, fast and greedy heuristics, Lagrangean heuristics, and various search techniques including simulated annealing, genetic algorithms, Tabu search and iterative constructive heuristics.

IE 416. Dynamic Programming (3)

The principle of optimality and recursive solution structure; multidimensional problems; reduction of dimensionality and approximation; stochastic control; nonserial systems; relationship to calculus of variation; applications. Prerequisite: IE 316 or equivalent.

IE 417. Nonlinear Optimization (3)

Advanced topics in mathematical optimization with emphasis on modeling and analysis of nonlinear problems. Convex analysis, unconstrained and constrained optimization, duality theory, Lagrangian relaxation, and methods for solving nonlinear optimization problems, including descent methods, Newton methods, conjugate gradient methods, and penalty and barrier methods. Prerequisite: IE 406 or equivalent.

IE 418. Discrete Optimization (3)

Advanced topics in mathematical optimization with emphasis on modeling and analysis of optimization problems with integer variables. Polyhedral theory, theory of valid inequalities, duality and relaxation, computational complexity, and methods for solving discrete optimization problems, such as branch and bound. Prerequisite: IE 406 or equivalent.

IE 419 Planning and Scheduling in Manufacturing and Services (3)

Models for the planning and scheduling of systems that produce goods or services. Resource allocation techniques utilizing static and dynamic scheduling methods and algorithms. Application areas include manufacturing and assembly systems, transportation system timetabling, project management, supply chains, and workforce scheduling. Prerequisites: IE 316 or equivalent

IE 422. Measurement and Inspection Systems (3)

Study of measurement instruments and sensors for manufactured products. Metrology standards, performance characteristics of measuring devices, calibration, error analysis, and gaging. Mechanical, optical, and other techniques. Online monitoring and control for product quality, and sensor integration and fusion. Prerequisite: IE 328 or equivalent.

IE 424. Robotic Systems and Applications (3)

Detailed analysis for robotic systems in manufacturing and service industries. Task planning and decomposition, motion trajectory analysis, conveyor tracking, error detection and recovery, end effector design, and systems integration. Prerequisite: IE 324 or consent of instructor.

IE 425. Advanced Inventory Theory (3)

Advanced analytical, algorithmic, and heuristic methods for optimizing and managing inventory systems. Economic order quantity model and extensions; power-of-two policies; base-stock and other policies for stochastic systems; the Clark-Scarf model; assembly and distribution systems; proofs of policy optimality. Prerequisites: IE 316 and IE 339, or equivalent.

IE 426. Optimization Models and Applications (3)

Modeling and analysis of operations research problems using techniques form mathematical programming. Linear programming, integer programming, multicriteria optimization, stochastic programming and nonlinear programming using an algebraic modeling language. This course is a version of IE 316 for graduate students, with research projects and advanced assignments. Closed to students who have taken IE 316. Prerequisite: IE 240 or equivalent.

IE 429. Stochastic Models and Applications (3)

Introduction to stochastic process modeling and analysis techniques and applications. Generalization of the Poisson process; renewal theory, queueing, and reliability; Brownian motion and stationary processes. This course is a version of IE 39 for graduate students, with research projects and advanced assignments. Closed to students who have taken IE 339. Prerequisite: IE 230 or equivalent.

IE 430. Management Science Project (3)

Analysis of a management problem and design of its solution incorporating management science techniques. An individual written report is required. Recommended to be taken in the last semester of the program.

IE 431. Operations Research Special Topics (3)

Extensive study of selected topics in techniques and models of operations research.

IE 433. Manufacturing Engineering Special Topics (3)

Extensive study of selected topics in the research and development of manufacturing engineering techniques.

IE 437. Advanced Database Analysis and Design (3)

Intensive treatment of design and application of modern database technology, including information modeling and logical design of databases. Emphasis on applications to the manufacturing environment. Prerequisite: IE 310 or equivalent.

IE 438. Advanced Data Communication Systems Analysis and Design (3)

Study of technological development, operational algorithms and performance analysis in data networks. Emphasis on recent developments in communication technologies, modeling and simulation of largescale networks, routing models and algorithms, and flow control issues. Prerequisite: IE 341 and IE 316, or equivalent.

IE 439. Queueing Systems (3)

Queueing theory and analysis of manufacturing, distribution, telecommunications, and other systems subject to congestion. Design and analysis of queueing networks; approximation methods such as mean value analysis, uniformization, fluid and diffusion interpretations; numerical solution approaches. Prerequisite: IE 339 or consent of instructor.

IE 441. Financial Engineering Projects (3)

Analysis, design and implementation of solutions to problems in financial services using information technology, mathematical modeling, and other financial engineering techniques. Emphasis on realworld problem solving, problem definition, implementation and solution evaluation.

IE 442. Manufacturing Management (3)

Study of factors affecting the development of a manufacturing management philosophy; decision-making process in areas of organization, planning, and control of manufacturing. The principles and techniques of TQM, Deming and others; metrics, costs, benchmarking, quality circles, and continuous improvement. Influence of the social, technical, and economic environment upon manufacturing management decisions. Case studies.

IE 443. (MSE 427) Automation and Production Systems (3)

Principles and analysis of manual and automated production systems for discrete parts and products. Cellular manufacturing, flexible manufacturing systems, transfer lines, manual and automated assembly systems, and quality control systems. Prerequisite: IE 215 or equivalent.

IE 445. Assembly Processes and Systems (3)

Joining processes including welding, brazing, soldering, and adhesive bonding. Mechanical assembly methods. Manual assembly lines and line balancing. Automated assembly. Product design considerations including Design for Assembly. Prerequisite: IE 215 or equivalent.

IE 446. Discrete Event Dynamic Systems (3)

Modeling of Discrete Event Dynamic systems (DEDS) particularly as applied to industrial systems. Modeling procedures with focus on Petri Nets. Hierarchical Petri Net modeling, performance analysis, behavioral and structural properties, and various synthesis and analytical techniques. Relationships to state space concepts, simulation, and finite state automata are introduced. Emphasis on use of such nets for the control of industrial systems. Prerequisites: Consent of instructor.

IE 447. Financial Optimization (3)

Making optimal financial decisions under uncertainty. Financial topics include asset/liability management, option pricing and hedging, risk management, and portfolio optimization. Optimization techniques covered include linear and nonlinear programming, integer programming, dynamic programming, and stochastic programming. Emphasis on use of modeling languages and solvers in financial applications. Requires basic knowledge of linear programming and probability. This course is a version of IE 347 for graduate students and requires advanced assignments. Credit will not be given for both IE 347 and IE 447. Prerequisite: IE 316 or IE 426 or equivalent.

IE 448. Industrial Control Systems for Manufacturing (3)

Techniques used to control manufacturing systems: numerical control, digital control, programmable logic controllers, and sensors.

IE 449. Advanced Computer Aided Manufacturing (3)

Numerical control in manufacturing; CAD/CAM systems; computer monitoring and control of manufacturing operations; adaptive control of manufacturing operations. Manufacturing resource planning, computeraided process planning, and shop floor control. Prerequisite: IE 340 or consent of instructor.

IE 451. Intelligent Manufacturing Systems (3)

Informational and control structures, architectures, and analysis techniques for autonomous and semiautonomous manufacturing systems. System architectures and techniques, knowledge based systems in production, and techniques based on fuzzy systems and neural networks. Applications in manufacturing systems control, process planning, and design and management problems in newly developing manufacturing and production systems. Prerequisite: Consent of instructor.

IE 455 Optimization Algorithms and Software (3)

Basic concepts of large families of optimization algorithms for both continuous and discrete optimization problems. Pros and cons of the various algorithms when applied to specific types of problems; information needed; whether local or global optimality can be expected. Participants practice with corresponding software tools to gain hands-on experience. This course is a version of IE 355 for graduate students and requires advanced assignments. Credit will not be given for both IE 355 and IE 455.

Prerequisite: IE 240 or consent of instructor

IE 458 (ECO 463). Topics in Game Theory (3)

A mathematical analysis of how people interact in strategic situations. Topics include normalform and extensiveform representations of games, various types of equilibrium requirements, the existence and characterization of equilibria, and mechanism design. The analysis is applied to microeconomic problems including industrial organization, international trade, and finance. Prerequisites: Two semesters of calculus, ECO 412 and ECO 414, or permission of the instructor.

IE 460. Engineering Project (1-3)

Intensive study of an area of industrial engineering with emphasis upon design and application. A written report is required.

IE 461. Readings (1-3)

Intensive study of some area of industrial engineering that is not covered in general courses.

IE 470. Introduction to Healthcare Systems (3)

The state of Healthcare from economic, systems, quality, and historical perspectives. Components of the Healthcare system including, facilities, delivery and treatment systems, and personnel. System costs, reimbursement methods and financial aspects in Healthcare. Healthcare policy, laws and ethics. System performance measures including access, cost effectiveness and quality of care.

IE 471. Quality and Process Improvement in Healthcare (3)

The dimensions of Healthcare quality and their definitions, quality metrics, accreditation and other benchmarking and evaluation methods. Change management, project planning and team management. Continuous improvement tools including “lean”, “six-sigma”, and “TQM”.

IE 472. Financial Management in Healthcare (3)

Engineering economics in Healthcare; value metrics (net present value, return on investment, etc.), cost-benefit analysis, capital projects and improvements. Accounting methods in Healthcare systems. Reimbursement methods, organizations, and alternatives. Financial strategy, planning, pricing and capital formation in “for”, and “not for” profit settings.

IE 473. Information Technology in Healthcare (3)

Introduction to information systems in Healthcare. Components of the system; electronic medical records, patient monitoring and data collection (clinical information systems), ancillaries (lab, pharmacy, radiology), imaging and digital technology, financial, inventory and management information systems. Enterprise systems in Healthcare, IT driven cost, efficiency and treatment quality metrics. Data warehousing, sharing, mining, protection and privacy issues.

IE 474. Healthcare Systems Engineering Capstone Project ()

A three credit hour “capstone” project to be completed in collaboration with industry partners and under the supervision of faculty. Students will work in small groups on projects in the Healthcare industry. The Professor of Practice is the general advisor for the capstone project course.

IE 475. Healthcare Systems Project (1-3)

Intensive study of an area of healthcare systems engineering with emphasis upon design and application. Written report is required.

IE 490. Thesis (16)

IE 499. Dissertation (115)

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